A Mechanistic Study of lncRNA Fendrr Regulation of FoxF1 Lung Cancer Tumor Supressor
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  • 关键词:lncRNAs ; Gene regulation ; Computational motif finding ; Data integration ; DNA ; lncRNA interaction
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2016
  • 出版时间:2016
  • 年:2016
  • 卷:9656
  • 期:1
  • 页码:781-789
  • 全文大小:438 KB
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  • 作者单位:Carmen Navarro (15)
    Carlos Cano (15)
    Marta Cuadros (16)
    Antonio Herrera-Merchan (17)
    Miguel Molina (18)
    Armando Blanco (15)

    15. Department of Computer Science and AI, University of Granada, Granada, Spain
    16. Department of Biochemistry and Molecular Biology, University of Granada, Granada, Spain
    17. GENyO, Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain
    18. Data Science Institute, Imperial College London, London, UK
  • 丛书名:Bioinformatics and Biomedical Engineering
  • ISBN:978-3-319-31744-1
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
文摘
Long non-coding RNAs are known to play multiple roles in the complex machinery of the cell. However, their recent addition to genomic research has increased the complexity of gene expression analyses. In this work, we perform a computational study that aims to contribute to the current understanding of the mechanisms that underlie the experimentally suggested interaction between the lncRNA Fendrr and FoxF1 lung cancer tumor suppressor in carcinogenesis. Results suggest that there exists indeed a multi-level interaction between Fendrr and FoxF1 promoter region, both direct via RNA-DNA:DNA triplex domain formation or mediated by proteins that interact simultaneously with the promoter region of FoxF1 and Fendrr transcripts. Moreover, the applied computational methodology can serve as a pipeline to process any candidate lncRNA-gene pair of interest and obtain putative sources of lncRNA-gene interaction.

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